Created by W.Langdon from gp-bibliography.bib Revision:1.7615

- @Article{DBLP:journals/rcs/ArellanoR19,
- author = "Humberto Velasco Arellano and Martin Montes Rivera",
- title = "Forward Kinematics for 2 {DOF} Planar Robot using Linear Genetic Programming",
- journal = "Research in Computing Science",
- volume = "148",
- number = "6",
- pages = "123--133",
- year = "2019",
- keywords = "genetic algorithms, genetic programming, forward kinematics, automatic robot modeling, linear genetic programming",
- ISSN = "1870-4069",
- URL = "https://www.rcs.cic.ipn.mx/2019_148_6/Forward%20Kinematics%20for%202%20DOF%20Planar%20Robot%20using%20Linear%20Genetic%20Programming.pdf",
- timestamp = "Wed, 17 Feb 2021 00:00:00 +0100",
- biburl = "https://dblp.org/rec/journals/rcs/ArellanoR19.bib",
- bibsource = "dblp computer science bibliography, https://dblp.org",
- size = "11 pages",
- abstract = "In the field of robotics, forward kinematics is an activity that allows finding a mathematical model for the resulting position in the final effector based on the robot joints position, a popular alternative for determining this model is defined by the Denavit Hartenberg convention, nevertheless, this method requires knowledge about linear algebra and three-dimensional spatial kinematics. Machine learning uses specific computational methodologies to solving similar problems in several areas, so it could be a viable answer for automatic determining of forwarding kinematics. we propose the use of genetic programming as a machine learning algorithm for finding the forward kinematics of a 2 degrees of freedom robot, getting a satisfactory outcome obtaining a satisfactory result with blocks that describe the expected solution, validating the capacity of the genetic programming in order to validate this algorithm for later work with more complex robots.",
- notes = "https://www.rcs.cic.ipn.mx/",
- }

Genetic Programming entries for Humberto Velasco Arellano Martin Montes Rivera